When it is desired to check the quality of a highway surfacing, the state of a section of highway can be inspected directly by the human eye. Such an inspection furnishes a very detailed analysis of the degradations of the surfacing. However, it will be understood that such a technique is extremely long and therefore extremely expensive to carry out. It is for this reason that it has been sought to develop techniques for automatically detecting such defects.
Among these known techniques may be mentioned the one consisting in placing on a vehicle a bar of CCD detectors whose axis of sight is perpendicular to the plane of the road. In this technique, the images taken by the optical sensor constitute a pavement of the highway. They are exploited to deduce therefrom the presence of a possible defect. However, such processes are relatively imprecise by reason, on the one hand, of the texture of the highway and, on the other hand, of the sensitivity to the conditions of illumination. In addition, they are relatively slow, particularly by reason of the acquisition and processing of high-definition images which correspond to large volumes of data.
Up to now, the problem of degradation of the highway surfacing has been considered However, it will be readily understood that a similar problem is encountered as soon as the surface on which it is desired to detect surface defects has a certain texture presenting a random optical appearance. This will be the case for example of the detection of defects in a fabric, or more precisely in a web of fabric or the case of the detection of possible defects in a surfacing web for example made of laminated material.
Another problem to be solved, in the case of exploiting an image for detecting a defect in a textured surface is that, if it is desired to analyze images corresponding to relatively large surfaces and if the defects are of relatively small dimensions, the problem of the definition of the optical sensor serving to make the shot is raised, in particular when the dimension of the defects may become of the order of a pixel or even smaller than a pixel. In that case, the detection of a defect will become very difficult or highly random, particularly due to the analog-digital conversion that it is necessary to effect to process the image obtained.
It is an object of the present invention to provide a process for detecting surface defects which allows a detection over a relatively large surface and with a relatively high speed of detection while ensuring a good quality of detection of the possible defects of this textured surface.